Vehicle Dynamics - Lateral: Open Source Simulation Package for MATLAB

Mendes, André de Souza; Meneghetti, Douglas De Rizzo; Ackermann, Marko; Fleury, Agenor de Toledo

doi:10.4271/2016-36-0115

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…However, this level of complexity does not suit the requirements for online application due to the excessive computational load. The model presented in this work is a simplified single-track model [55], which is commonly used in studies of different controllers/methods related to car-like systems due to its simplicity and accurate representation of the dynamic behaviors of a car. The state-space model is as follows:…”

Section: Appendix a Vehicle Dynamic Modelmentioning

confidence: 99%

A Fast and Close-to-Optimal Receding Horizon Control for Trajectory Generation in Dynamic Environments

2022

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This paper presents a new approach for the optimal trajectory planning of nonlinear systems in a dynamic environment. Given the start and end goals with an objective function, the problem is to find an optimal trajectory from start to end that minimizes the objective while taking into account the changes in the environment. One of the main challenges here is that the optimal control sequence needs to be computed in a limited amount of time and needs to be adapted on-the-fly. The control method presented in this work has two stages: the first-order gradient algorithm is used at the beginning to compute an initial guess of the control sequence that satisfies the constraints but is not yet optimal; then, sequential action control is used to optimize only the portion of the control sequence that will be applied on the system in the next iteration. This helps to reduce the computational effort while still being optimal with regard to the objective; thus, the proposed approach is more applicable for online computation as well as dealing with dynamic environments. We also show that under mild conditions, the proposed controller is asymptotically stable. Different simulated results demonstrate the capability of the controller in terms of solving various tracking problems for different systems under the existence of dynamic obstacles. The proposed method is also compared to the related indirect optimal control approach and sequential action control in terms of cost and computation time to evaluate the improvement of the proposed method.

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Section: Appendix a Vehicle Dynamic Modelmentioning

confidence: 99%

A Fast and Close-to-Optimal Receding Horizon Control for Trajectory Generation in Dynamic Environments

2022

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“…Even with computational tools that apply sophisticated techniques for vehicle dynamics simulation, simplified models continue to be widely explored due to their practicality in specific applications. For example, in [1], a vehicle dynamics simulation tool was developed using simplified models, providing an alternative for researchers and developers to expensive commercial software.…”

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confidence: 99%

Analysis and Virtual Validation of Vehicle Dynamics Models for Electronic Stability Control

Alves Torres,

Murilo,

Vilela Lopes

et al. 2024

IEEE Latin Am. Trans.

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This work investigates the utility and efficiency of simplified vehicle dynamics models in the Electronic Stability Control (ESC) context. The focus is not merely on the correlation between simplified and complex models but on the added value such models can bring to the automotive industry. By comparing the simplified models based on bicycle representation with a high-fidelity VI-CarRealTime (VI-CRT) model, this paper demonstrates that the simplified models have good correlation and offer computational advantages. This approach addresses the key dynamics essential for ESC and considers a generic sedan vehicle model to simulate standard maneuvers widely performed by the automotive industry. All the proposed models are nonlinear and include tire modeling based on the Magic Formula, with parameters derived from experimental tests. The paper also introduces a methodology for parameter optimization, enhancing the model's accuracy and reliability. The results indicate that the simplified models can be a viable alternative for specific applications such as control strategy tuning, rapid prototyping, and early-stage development. This work aims to fill the gap in the literature concerning the practical applicability and limitations of simplified vehicle dynamics models, thereby making a significant contribution to the field.

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Data-driven safe control via finite-time Koopman identifier

Mazouchi,

Modares

2023

International Journal of Control

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Vehicle Dynamics - Lateral: Open Source Simulation Package for MATLAB

Cited by 5 publications

References 8 publications

A Fast and Close-to-Optimal Receding Horizon Control for Trajectory Generation in Dynamic Environments

A Fast and Close-to-Optimal Receding Horizon Control for Trajectory Generation in Dynamic Environments

Analysis and Virtual Validation of Vehicle Dynamics Models for Electronic Stability Control

Data-driven safe control via finite-time Koopman identifier

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